Exact-corrected confidence interval for risk difference in noninferiority binomial trials

TL;DR

This paper introduces a new confidence interval estimator for risk difference in noninferiority binomial trials, offering improved accuracy and power, especially for small samples, supported by theoretical justification and simulations.

Contribution

It presents an exact-corrected confidence interval method that aligns with an unconditional test, enhancing existing approaches for noninferiority binomial trials.

Findings

Improved power for small sample sizes

Theoretically justified accuracy

Effective in simulations and real examples

Abstract

A novel confidence interval estimator is proposed for the risk difference in noninferiority binomial trials. The confidence interval is consistent with an exact unconditional test that preserves the type-I error, and has improved power, particularly for smaller sample sizes, compared to the confidence interval by Chan & Zhang (1999). The improved performance of the proposed confidence interval is theoretically justified and demonstrated with simulations and examples. An R package is also distributed that implements the proposed methods along with other confidence interval estimators.